PROJECT SUMMARY Nearly 37,000 new cases of oral cancer will be diagnosed in the United States in 2019, and nearly half will die in 5 years. The lethality of this disease is partially attributed to the fact that most cases are in advanced stages when diagnosed. Surgical resection remains a primary modality for treatment but local and regional recurrence remains the most common problem after surgical resection; patients with advanced stage oral cancer experience recurrence rates as high as 60-80% in the first 3 years. Inadequate tumor excision is a common cause for such local recurrence. This could be explained by the imprecise methods currently used for assessing surgical margins and by the presence of ?satellite? malignant cells (?skip lesions?) in sites away from the primary cancerous lesion which occur as a result of the ?field cancerization? phenomenon. Currently, surgeons often depend on their own judgment or visualization under white light to determine surgical margins. Confirmation of negative margins is based on randomly selected samples for intraoperative frozen section analysis, leaving much of the surgical margin unexamined. Moreover, frozen section analysis can be time consuming, expensive, and have a high false negative rate. A more efficient and precise approach is needed. Optical technologies can be used to distinguish in situ benign from malignant tissue lesions. Elastic Scattering Spectroscopy (ESS) is a point spectroscopic measuring technique that can detect with great sensitivity sub-cellular morphologic differences between benign and malignant tissue. These differences include nuclear size, chromatin granularity or density, organelle sizes and densities, and other sub-cellular features. ESS provides the advantage of real-time, objective and quick assessment of tissue morphology; the optical-spectroscopy equivalent of histopathological readings. Past research demonstrated the ability of ESS to differentiate with good precision normal versus abnormal oral mucosa, in-vivo, during oral cancer surgical resection. The first aim of this current study is to expand on that work by further training the ESS algorithms on a much larger prospective dataset so that the technology can demonstrate clinically acceptable accuracy standards. The second aim of this study is to design and test novel instrumentation capable of differentiating between normal and abnormal tissue on both aspects of the deep margin (tumor and tumor bed). One hundred and twenty patients will be enrolled from Boston Medical Center and from the Boston VA hospitals. ESS measures will be co-registered with histopathological assessments of dysplasia grade and inflammation type. Further refinement of this technology will result in the validation of ESS instrumentation capable of facilitating intraoperative margin guidance. Our hypothesis is that further refinement of our ESS algorithms will greatly improve surgeons' accuracy in determining which tissue should go to frozen section, and will help the surgeon assess proper surgical margins during excision of oral cancers compared to traditional approaches alone. This, in turn, will significantly reduce local recurrence rates and its associated morbidity and mortality.